Top 10 Open-Source User Interfaces for LLMs

Source: Dev.to

Overview

Open‑source user interfaces for large language models (LLMs) are empowering developers, researchers, and businesses to interact with AI models locally and securely. These UIs offer everything from simple chat interfaces to advanced agent frameworks, supporting a wide range of models and deployment scenarios. In 2025 the landscape is richer than ever, with options tailored for privacy, customization, and rapid prototyping. This guide covers the 10 best open‑source UIs for LLMs, their standout features, and direct links to their repositories.

1. Open WebUI

Open WebUI is a self‑hosted, extensible AI interface that supports Ollama, OpenAI API, and various LLM runners. It features granular permissions, responsive design, full Markdown/LaTeX support, hands‑free voice/video calls, native Python function calling, persistent artifact storage, local RAG integration, web search, image generation/editing, and enterprise authentication. Ideal for privacy‑focused deployments, local model experimentation, and enterprise use cases.

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2. LobeChat

LobeChat is a modern, open‑source ChatGPT‑like UI with support for speech synthesis, multimodal input, a plugin system, an agent marketplace, and one‑click deployment. It supports MCP (Model Context Protocol), smart internet search, chain‑of‑thought visualization, branching conversations, artifacts, file upload/knowledge base, multiple model providers, local LLMs (Ollama), visual recognition, TTS/STT, text‑to‑image generation, and custom themes. LobeChat excels in extensibility, user experience, and rapid deployment for both individuals and teams.

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3. Text Generation Web UI

Text Generation Web UI is a popular open‑source platform for running and interacting with local LLMs. It supports a wide range of models, offers a clean interface, and includes advanced features like model presets, plugins, and community‑driven enhancements. Favoured by developers and researchers for local experimentation and model benchmarking.

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4. Chatbot UI

Chatbot UI is a Next.js‑based, open‑source chat interface that supports OpenAI and Azure APIs. Designed for easy self‑hosting, customization, and rapid prototyping, it’s a go‑to choice for developers building custom chatbot experiences.

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5. LibreChat

LibreChat is an open‑source, multi‑provider chat UI with support for MCP, rich UI features, and a focus on privacy. It’s built for users who want a versatile, self‑hosted chat experience with advanced agent orchestration and workflow management.

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6. AnythingLLM

AnythingLLM is a multi‑model, MCP‑compatible UI that supports both local and cloud deployment. Known for its flexibility, privacy, and ease of use, it suits personal as well as enterprise AI workflows.

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7. Flowise

Flowise is a visual builder for LangChain‑based LLM applications. It enables users to create complex agent workflows and pipelines with drag‑and‑drop ease, ideal for developers and non‑developers alike.

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8. LangFlow

LangFlow is a visual pipeline builder for LangChain, allowing users to design, prototype, and deploy LLM‑powered workflows. Perfect for rapid experimentation and building complex agent logic.

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9. assistant‑ui

assistant‑ui is a React/TypeScript component library for building custom LLM chat interfaces. Highly modular and customizable, it’s a favorite for developers crafting tailored agent experiences.

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10. Streamlit

Streamlit is a Python‑based framework for quickly building and deploying interactive web apps, including LLM chat interfaces. Ideal for rapid prototyping, data‑science workflows, and AI experimentation.

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How to Use These UIs

• Most can be self‑hosted with Docker or via simple npm/pip installations.
• They support local models (via Ollama, llama.cpp, etc.) and cloud APIs (OpenAI, Anthropic, Azure).
• Many offer advanced features such as Retrieval‑Augmented Generation (RAG), agent orchestration, multimodal support, and MCP compatibility.

Conclusion

Open‑source UIs for LLMs are essential tools for anyone building, experimenting, or deploying AI agents. From simple chat interfaces to full‑featured agent frameworks, these projects provide flexibility, privacy, and a vibrant community‑driven ecosystem.

en innovation. Whether you’re a developer, researcher, or entrepreneur, exploring these UIs can unlock new possibilities for your AI workflows in 2025 and beyond.

Thank you so much for reading

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